In-ground sensor systems with modular sensors and wireless connectivity components

ABSTRACT

In an embodiment, an integrated sensor system with modular sensors and wireless connectivity components for monitoring properties of field soil is described. In an embodiment, an integrated sensor system comprises one or more sensors that are configured to determine one or more measures of at least one property of soil. The integrated sensor system also includes one or more processing units that are configured to receive, from the sensors, the measures of at least one property of soil and calculate soil property data based on the measures. The system further includes a transmitter that is configured to receive the soil property data from the processing units, establish a communications connection with at least one computer device, and automatically transmit the soil property data to the at least one computer device via the communications connection. In an embodiment, the communications connection is a wireless connection established between the transmitter and a smart hub or a LoRA-enabled device. In an embodiment, the computer sensors, the processors, and the transmitter are installed inside a portable probe.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.16/660,402, filed on Oct. 22, 2019, which claims the priority of U.S.Provisional Application No. 62/750,129, filed Oct. 24, 2018, the entirecontents of each of which are incorporated herein by reference.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the Patent and TrademarkOffice patent file or records, but otherwise reserves all copyright orrights whatsoever. © 2015-2019 The Climate Corporation.

FIELD OF THE DISCLOSURE

One technical field of the present disclosure is field soil measurementsin agriculture including sensors and processing units to calculate soilproperty data for an agricultural field, and data communicationstransmitters to wirelessly transmit the soil property data to computerdevices.

BACKGROUND

The approaches described in this section are approaches that could bepursued, but not necessarily approaches that have been previouslyconceived or pursued. Therefore, unless otherwise indicated, it shouldnot be assumed that any of the approaches described in this sectionqualify as prior art merely by virtue of their inclusion in thissection. Further, it should not be assumed that any of the approachesdescribed in this section are well-understood, routine, or conventionalmerely by virtue of their inclusion in this section.

Crop growers and agronomists monitor amounts of nutrients in soil anduse the nutrient information to improve agricultural practices for thesoil. The monitoring process is, however, difficult because nutrientamounts in soil vary from one location to another. Furthermore, theamounts may vary with the sampling time, environmental conditions, andsoil physical characteristics. The monitoring process also may bedifficult because collecting the soil samples and sending them tolaboratories is labor-intensive, and because receiving the results fromlaboratories takes several weeks.

Furthermore, the monitoring process may be inefficient because resultsreceived from the laboratories may be inaccurate. Since soil propertiessuch as temperature, moisture, and nitrate fluctuate over time,infrequently collected soil samples rarely capture changes in the soilproperties correctly. Thus, relying on results received fromlaboratories makes understanding and quantifying the changes quitechallenging.

SUMMARY

The appended claims may serve as a summary of the disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings:

FIG. 1 depicts an example computer system that is configured to performthe functions described herein, shown in a field environment with otherapparatus with which the system may interoperate.

FIG. 2 depicts two views of an example logical organization of sets ofinstructions in main memory when an example mobile application is loadedfor execution.

FIG. 3 depicts a programmed process by which the agriculturalintelligence computer system generates one or more preconfiguredagronomic models using agronomic data provided by one or more datasources.

FIG. 4 is a block diagram that illustrates a computer system upon whichan embodiment of the invention may be implemented.

FIG. 5 depicts an example embodiment of a timeline view for data entry.

FIG. 6 depicts an example embodiment of a spreadsheet view for dataentry.

FIG. 7 depicts an example in-ground sensor system with modular sensorsand wireless connectivity components that is configured to determinefield properties in soil.

FIG. 8 depicts an example process that uses an in-ground sensor systemwith modular sensors and wireless connectivity components that isconfigured to determine field properties in soil.

FIG. 9A depicts an example in-ground sensor system implemented in ahandheld device and comprising modular sensors, processors, and wirelessconnectivity components.

FIG. 9B depicts two views of an example in-ground moisture andtemperature sensor system implemented in an in-ground blade andcomprising modular sensors, processors, and wireless connectivitycomponents.

FIG. 9C depicts an example in-ground sensor system comprising modularsensors, processors, and wireless connectivity components.

FIG. 9D depicts an example in-ground nitrate, moisture, and temperaturesensor system implemented in an in-ground blade and comprising modularsensors, processors, and wireless connectivity components.

FIG. 9E depicts an example in-ground sensor system that includes asystem identifier.

FIG. 9F depicts an example in-ground sensor system that includes atransceiver.

DETAILED DESCRIPTION

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present disclosure. It will be apparent, however,that embodiments may be practiced without these specific details. Inother instances, well-known structures and devices are shown in blockdiagram form in order to avoid unnecessarily obscuring the presentdisclosure. Embodiments are disclosed in sections according to thefollowing outline:

-   -   1. GENERAL OVERVIEW    -   2. EXAMPLE AGRICULTURAL INTELLIGENCE COMPUTER SYSTEM        -   2.1. STRUCTURAL OVERVIEW        -   2.2. APPLICATION PROGRAM OVERVIEW        -   2.3. DATA INGEST TO THE COMPUTER SYSTEM        -   2.4. PROCESS OVERVIEW—AGRONOMIC MODEL TRAINING        -   2.5. SOIL ANALYSIS        -   2.6. IMPLEMENTATION EXAMPLE—HARDWARE OVERVIEW    -   3. IN-GROUND SENSOR SYSTEMS WITH MODULAR SENSORS AND WIRELESS        CONNECTIVITY COMPONENTS        -   3.1. SYSTEM OVERVIEW        -   3.2. PROCESS OVERVIEW    -   4. EXAMPLE IMPLEMENTATIONS        -   4.1. HANDHELD INTEGRATED SENSOR SYSTEMS        -   4.2. BLADE-BASED INTEGRATED SENSOR SYSTEMS    -   5. EXTENSIONS AND ALTERNATIVES    -   6. IMPROVEMENTS PROVIDED BY CERTAIN EMBODIMENTS

1. General Overview

In one embodiment, an in-ground, integrated sensor system with modularsensors and communications connectivity components is described. Theintegrated sensor system may be used to calculate soil property data ofsoil properties in a field, and to transmit the soil property data tostorage systems and computer devices. The system may be installed in thefield and may be configured to measure the soil properties on-demand,according to a time schedule, and throughout a prolonged period of time.The integrated sensor system may be configured to transmit the soilproperty data to other devices via wireless communications connectionsestablished between the system and the devices. The versatility andconvenience of the integrated system allows overcoming the shortcomingsof conventional systems because the integrated system does not requiresending physical soil samples to laboratories or awaiting receiving thesoil property data from the laboratories.

In an embodiment, an integrated sensor system comprises one or moresensors, one or more processing units, and one or more communicationsdevices. The sensors, processing units, and communications devices maybe enclosed or sealed in a probe, or a container, which may protect thesensors, processors, and devices from dust, moisture, and otherelements. The probe may be inserted into a cavity created in soil toallow the sensors measure soil properties as soon as the sensors are incontact with the soil. Examples of the soil properties may includenitrate concentrations, nitrite concentrations, ammonium concentrations,ammonia concentrations, sulfate concentrations, sulfite concentrations,iron concentrations, micronutrient concentrations, chlorideconcentrations, phosphorus concentrations, chlorine concentrations, pHlevels, moisture levels, temperature, soil bulk density, orprecipitation levels.

An integrated sensor system may be implemented in many types of portabledevices, such as handheld devices, in-ground blades, or other devicesthat may be inserted into soil. The system may be powered up byconventional batteries and/or solar panels. Once the system is insertedinto a cavity in the soil, adjusted in the soil to a desired depth, andpowered up, the system may start measuring the soil properties.

To determine soil property data for soil, the integrated sensor systemmay use one or more sensors that are configured to measure soilproperties in the soil. Examples of sensors may include capacitivemoisture sensors, time-domain reflectometry moisture sensors,temperature sensors, and nitrate sensors. Each of the sensors mayprovide the measures to one or more processing units, and the processingunits may use the received measures to calculate the soil property data.The soil property data may indicate, for example, a nitrateconcentration level, a chloride concentration level, a phosphorusconcentration level, a chlorine concentration level, a pH level, amoisture level, temperature, and/or a precipitation level.

An integrated sensor system may include additional devices, such as oneor more imaging sensors, one or more anemometers, and one or morerainfall sensors. An imaging sensor may be also equipped with a digitalcamera or a video camera that is not lodged in a cavity in the ground,and that is configured to capture images of the scenery that the sensorcan detect in its field of view. The anemometer may be used to, forexample, measure the wind at the location where the integrated sensorsystem is installed.

The soil property data, and the additional data if such is provided, maybe transmitted from the integrated sensor system to other devices. Totransmit the data, the integrated sensor system may use one or moreelectronic data transmitters or transceivers that may be installed inthe integrated system. Each transmitter may comprise an electronicdevice that is configured to establish a communications connection withanother device and transmit data to that device, but it cannot receivedata from another device. Each transceiver may comprise an electronicdevice that is configured to not only establish a communicationsconnection with another device and transmit data to that device, butalso to receive electronic data from devices. Hence, a transceiver is adevice that provides functionalities of both a transmitter and areceiver. A communications connection established by a transmitter or atransceiver of an integrated sensor system may be any type ofcommunications connection, including a wireless communicationsconnection established in compliance with, for example, the Bluetoothcommunications protocol, or a radio-frequency (“RF”) wirelesscommunications protocol. In some embodiments, the transmitter or thetransceiver may use wired communications connections of local areanetworks or wide area networks.

Upon establishing a communications connection with another device, thetransmitter, or the transceiver, of the integrated system may transmitto the device the soil property data and additional data if such isavailable. This may include transmitting the soil property data to astorage device for storing and further processing. Examples of storagedevices may include cloud-based storage systems, data servers, and datarepository servers.

The soil property data may be transmitted to user devices, such aslaptops, personal computers, mobile devices, tablets, smartphones, andthe like. Upon receiving the soil property data, the user devices may beused to generate graphical representations of the data, display thegraphical representations of the data on display devices, use the datato update agricultural data repositories, and/or transmit the data tocomputer-based controllers to control agricultural equipment.

In an embodiment, an integrated sensor system is assigned a universallyunique identifier (“UUID”). The UUID may be used to identify a type anda location of the integrated sensor system. The UUID may be stored inone of the sensors or a memory unit included in the integrated sensorsystem or may be printed on a physical medium attached to the integratedsensor system. For example, the UUID may be encoded in a quick response(QR) code, and the QR code may be printed on a laminated label which maybe affixed on a top portion of the integrated system. The UUIDinformation may be included in soil property data that the integratedsensor system transmits to computer devices. A UUID may be determined byinspecting data that is received from the integrated system. Forexample, upon receiving the soil property data from the integratedsystem, the received data may be parsed, and an UUID may be extractedfrom the parsed data. Based on the extracted UUID, a type and a locationof the integrated system may be determined. The UUID information may beused to, for example, associate the received soil property data with thelocation that corresponds to the UUID of the integrated system. The UUIDinformation may also be used to associate the sensor with manufacturingor calibration data that is used to process the raw data into acalibrated soil property measurement. The association between the soilproperty data and the location of the integrated system may be stored ina data repository maintained for the field.

The process of associating soil property data with locations may berepeated each time soil property data is received from any of multipleintegrated systems installed throughout a field. The associations may bestored in a data repository and may be used to generate graphicalrepresentations of the associations and displayed on display devices.The graphical representations may depict, for example, concentrationlevels of nitrate, chlorine, pH, phosphorus, or other matter throughoutthe field, and may be used to generate improved agricultural andirrigation practices for the field.

The ability to perform the content analysis of soil using an integratedsensor system with modular sensors and wireless connectivity componentsprovides convenience and versatility. For example, a crop grower may usea plurality of integrated sensor systems installed throughout the fieldto determine concentration levels of nitrate at various location withinthe field and may do so as frequently as needed to monitor the rapidlychanging levels of nitrate throughout the field. Based on themonitoring, the grower may modify fertilization prescriptions for thefield as frequently as needed. For example, the grower may use soilproperty data received from the integrated systems to determine optimalschedules for cultivating the field, appropriate amounts of fertilizerfor the filed, and appropriate timetables for applying fertilizers tothe field.

Integrated sensor systems with modular sensors and wireless connectivitycomponents may be used by agronomical researchers and developers workingin technological centers. The researchers may use the provided soilproperty data to develop new seed varieties, enhance fertilizationtechniques, and develop enhancements to irrigation technologies. Thereceived soil property data may be also used to monitor the fields witha high vulnerability to chemical pollution, and to develop strategiesand environment-aware practices for handling the soil nutrient losses.

The soil property data may be provided to computer-based controllersthat control agricultural equipment operating in the field. For example,the information that includes both nitrate concentration information forthe soil and an UUID of the integrated sensor system that determined thenitrate concentration in the soil may be used by a computer-basedcontroller installed on a fertilizer machine to either increase ordecrease the amount of fertilizer as the fertilizer machine applies thefertilizer to the soil.

2. Example Agricultural Intelligence Computer System

2.1 Structural Overview

FIG. 1 illustrates an example computer system that is configured toperform the functions described herein, shown in a field environmentwith other apparatus with which the system may interoperate. In oneembodiment, a user 102 owns, operates or possesses a field managercomputing device 104 in a field location or associated with a fieldlocation such as a field intended for agricultural activities or amanagement location for one or more agricultural fields. The fieldmanager computer device 104 is programmed or configured to provide fielddata 106 to an agricultural intelligence computer system 130 via one ormore networks 109.

Examples of field data 106 include (a) identification data (for example,acreage, field name, field identifiers, geographic identifiers, boundaryidentifiers, crop identifiers, and any other suitable data that may beused to identify farm land, such as a common land unit (CLU), lot andblock number, a parcel number, geographic coordinates and boundaries,Farm Serial Number (FSN), farm number, tract number, field number,section, township, and/or range), (b) harvest data (for example, croptype, crop variety, crop rotation, whether the crop is grownorganically, harvest date, Actual Production History (APH), expectedyield, yield, crop price, crop revenue, grain moisture, tillagepractice, and previous growing season information), (c) soil data (forexample, type, composition, pH, organic matter (OM), cation exchangecapacity (CEC)), (d) planting data (for example, planting date, seed(s)type, relative maturity (RM) of planted seeds, seed population), (e)fertilizer data (for example, nutrient type (Nitrogen, Phosphorus,Potassium), application type, application date, amount, source, method),(f) chemical application data (for example, pesticide, herbicide,fungicide, other substance or mixture of substances intended for use asa plant regulator, defoliant, or desiccant, application date, amount,source, method), (g) irrigation data (for example, application date,amount, source, method), (h) weather data (for example, precipitation,rainfall rate, predicted rainfall, water runoff rate region,temperature, wind, forecast, pressure, visibility, clouds, heat index,dew point, humidity, snow depth, air quality, sunrise, sunset), (i)imagery data (for example, imagery and light spectrum information froman agricultural apparatus sensor, camera, computer, smartphone, tablet,unmanned aerial vehicle, planes or satellite), (j) scouting observations(photos, videos, free form notes, voice recordings, voicetranscriptions, weather conditions (temperature, precipitation (currentand over time), soil moisture, crop growth stage, wind velocity,relative humidity, dew point, black layer)), and (k) soil, seed, cropphenology, pest and disease reporting, and predictions sources anddatabases.

A data server computer 108 is communicatively coupled to agriculturalintelligence computer system 130 and is programmed or configured to sendexternal data 110 to agricultural intelligence computer system 130 viathe network(s) 109. The external data server computer 108 may be ownedor operated by the same legal person or entity as the agriculturalintelligence computer system 130, or by a different person or entitysuch as a government agency, non-governmental organization (NGO), and/ora private data service provider. Examples of external data includeweather data, imagery data, soil data, or statistical data relating tocrop yields, among others. External data 110 may consist of the sametype of information as field data 106. In some embodiments, the externaldata 110 is provided by an external data server 108 owned by the sameentity that owns and/or operates the agricultural intelligence computersystem 130. For example, the agricultural intelligence computer system130 may include a data server focused exclusively on a type of data thatmight otherwise be obtained from third party sources, such as weatherdata. In some embodiments, an external data server 108 may actually beincorporated within the system 130.

An agricultural apparatus 111 may have one or more remote sensors 112fixed thereon, which sensors are communicatively coupled either directlyor indirectly via agricultural apparatus 111 to the agriculturalintelligence computer system 130 and are programmed or configured tosend sensor data to agricultural intelligence computer system 130.Examples of agricultural apparatus 111 include tractors, combines,harvesters, planters, trucks, fertilizer equipment, aerial vehiclesincluding unmanned aerial vehicles, and any other item of physicalmachinery or hardware, typically mobile machinery, and which may be usedin tasks associated with agriculture. In some embodiments, a single unitof apparatus 111 may comprise a plurality of sensors 112 that arecoupled locally in a network on the apparatus; controller area network(CAN) is example of such a network that can be installed in combines,harvesters, sprayers, and cultivators. Application controller 114 iscommunicatively coupled to agricultural intelligence computer system 130via the network(s) 109 and is programmed or configured to receive one ormore scripts that are used to control an operating parameter of anagricultural vehicle or implement from the agricultural intelligencecomputer system 130. For instance, a controller area network (CAN) businterface may be used to enable communications from the agriculturalintelligence computer system 130 to the agricultural apparatus 111, suchas how the CLIMATE FIELDVIEW DRIVE, available from The ClimateCorporation, San Francisco, California, is used. Sensor data may consistof the same type of information as field data 106. In some embodiments,remote sensors 112 may not be fixed to an agricultural apparatus 111 butmay be remotely located in the field and may communicate with network109.

The apparatus 111 may comprise a cab computer 115 that is programmedwith a cab application, which may comprise a version or variant of themobile application for device 104 that is further described in othersections herein. In an embodiment, cab computer 115 comprises a compactcomputer, often a tablet-sized computer or smartphone, with a graphicalscreen display, such as a color display, that is mounted within anoperator's cab of the apparatus 111. Cab computer 115 may implement someor all of the operations and functions that are described further hereinfor the mobile computer device 104.

The network(s) 109 broadly represent any combination of one or more datacommunication networks including local area networks, wide areanetworks, internetworks or internets, using any of wireline or wirelesslinks, including terrestrial or satellite links. The network(s) may beimplemented by any medium or mechanism that provides for the exchange ofdata between the various elements of FIG. 1 . The various elements ofFIG. 1 may also have direct (wired or wireless) communications links.The sensors 112, controller 114, external data server computer 108, andother elements of the system each comprise an interface compatible withthe network(s) 109 and are programmed or configured to use standardizedprotocols for communication across the networks such as TCP/IP,Bluetooth, CAN protocol and higher-layer protocols such as HTTP, TLS,and the like.

Agricultural intelligence computer system 130 is programmed orconfigured to receive field data 106 from field manager computing device104, external data 110 from external data server computer 108, andsensor data from remote sensor 112. Agricultural intelligence computersystem 130 may be further configured to host, use or execute one or morecomputer programs, other software elements, digitally programmed logicsuch as FPGAs or ASICs, or any combination thereof to performtranslation and storage of data values, construction of digital modelsof one or more crops on one or more fields, generation ofrecommendations and notifications, and generation and sending of scriptsto application controller 114, in the manner described further in othersections of this disclosure.

In an embodiment, agricultural intelligence computer system 130 isprogrammed with or comprises a communication layer 132, presentationlayer 134, data management layer 140, hardware/virtualization layer 150,and model and field data repository 160. “Layer,” in this context,refers to any combination of electronic digital interface circuits,microcontrollers, firmware such as drivers, and/or computer programs orother software elements.

Communication layer 132 may be programmed or configured to performinput/output interfacing functions including sending requests to fieldmanager computing device 104, external data server computer 108, andremote sensor 112 for field data, external data, and sensor datarespectively. Communication layer 132 may be programmed or configured tosend the received data to model and field data repository 160 to bestored as field data 106.

Presentation layer 134 may be programmed or configured to generate agraphical user interface (GUI) to be displayed on field managercomputing device 104, cab computer 115 or other computers that arecoupled to the system 130 through the network 109. The GUI may comprisecontrols for inputting data to be sent to agricultural intelligencecomputer system 130, generating requests for models and/orrecommendations, and/or displaying recommendations, notifications,models, and other field data.

Data management layer 140 may be programmed or configured to manage readoperations and write operations involving the repository 160 and otherfunctional elements of the system, including queries and result setscommunicated between the functional elements of the system and therepository. Examples of data management layer 140 include JDBC, SQLserver interface code, and/or HADOOP interface code, among others.Repository 160 may comprise a database. As used herein, the term“database” may refer to either a body of data, a relational databasemanagement system (RDBMS), or to both. As used herein, a database maycomprise any collection of data including hierarchical databases,relational databases, flat file databases, object-relational databases,object-oriented databases, distributed databases, and any otherstructured collection of records or data that is stored in a computersystem. Examples of RDBMS's include, but are not limited to including,ORACLE®, MYSQL, IBM® DB2, MICROSOFT® SQL SERVER, SYBASE®, and POSTGRESQLdatabases. However, any database may be used that enables the systemsand methods described herein.

When field data 106 is not provided directly to the agriculturalintelligence computer system via one or more agricultural machines oragricultural machine devices that interacts with the agriculturalintelligence computer system, the user may be prompted via one or moreuser interfaces on the user device (served by the agriculturalintelligence computer system) to input such information. In an exampleembodiment, the user may specify identification data by accessing a mapon the user device (served by the agricultural intelligence computersystem) and selecting specific CLUs that have been graphically shown onthe map. In an alternative embodiment, the user 102 may specifyidentification data by accessing a map on the user device (served by theagricultural intelligence computer system 130) and drawing boundaries ofthe field over the map. Such CLU selection or map drawings representgeographic identifiers. In alternative embodiments, the user may specifyidentification data by accessing field identification data (provided asshape files or in a similar format) from the U. S. Department ofAgriculture Farm Service Agency or other source via the user device andproviding such field identification data to the agriculturalintelligence computer system.

In an example embodiment, the agricultural intelligence computer system130 is programmed to generate and cause displaying a graphical userinterface comprising a data manager for data input. After one or morefields have been identified using the methods described above, the datamanager may provide one or more graphical user interface widgets whichwhen selected can identify changes to the field, soil, crops, tillage,or nutrient practices. The data manager may include a timeline view, aspreadsheet view, and/or one or more editable programs.

FIG. 5 depicts an example embodiment of a timeline view for data entry.Using the display depicted in FIG. 5 , a user computer can input aselection of a particular field and a particular date for the additionof event. Events depicted at the top of the timeline may includeNitrogen, Planting, Practices, and Soil. To add a nitrogen applicationevent, a user computer may provide input to select the nitrogen tab. Theuser computer may then select a location on the timeline for aparticular field in order to indicate an application of nitrogen on theselected field. In response to receiving a selection of a location onthe timeline for a particular field, the data manager may display a dataentry overlay, allowing the user computer to input data pertaining tonitrogen applications, planting procedures, soil application, tillageprocedures, irrigation practices, or other information relating to theparticular field. For example, if a user computer selects a portion ofthe timeline and indicates an application of nitrogen, then the dataentry overlay may include fields for inputting an amount of nitrogenapplied, a date of application, a type of fertilizer used, and any otherinformation related to the application of nitrogen.

In an embodiment, the data manager provides an interface for creatingone or more programs. “Program,” in this context, refers to a set ofdata pertaining to nitrogen applications, planting procedures, soilapplication, tillage procedures, irrigation practices, or otherinformation that may be related to one or more fields, and that can bestored in digital data storage for reuse as a set to be used in otheroperations. After a program has been created, it may be conceptuallyapplied to one or more fields and references to the program may bestored in digital storage in association with data identifying thefields. Thus, instead of manually entering identical data relating tothe same nitrogen applications for multiple different fields, a usercomputer may create a program that indicates a particular application ofnitrogen and then apply the program to multiple different fields. Forexample, in the timeline view of FIG. 5 , the top two timelines have the“Spring applied” program selected, which includes an application of 150lbs N/ac in early April. The data manager may provide an interface forediting a program. In an embodiment, when a particular program isedited, each field that has selected the particular program is edited.For example, in FIG. 5 , if the “Spring applied” program is edited toreduce the application of nitrogen to 130 lbs. N/ac, the top two fieldsmay be updated with a reduced application of nitrogen based on theedited program.

In an embodiment, in response to receiving edits to a field that has aprogram selected, the data manager removes the correspondence of thefield to the selected program. For example, if a nitrogen application isadded to the top field in FIG. 5 , the interface may update to indicatethat the “Spring applied” program is no longer being applied to the topfield. While the nitrogen application in early April may remain, updatesto the “Spring applied” program would not alter the April application ofnitrogen.

FIG. 6 depicts an example embodiment of a spreadsheet view for dataentry. Using the display depicted in FIG. 6 , a user can create and editinformation for one or more fields. The data manager may includespreadsheets for inputting information with respect to Nitrogen,Planting, Practices, and Soil as depicted in FIG. 6 . To edit aparticular entry, a user computer may select the particular entry in thespreadsheet and update the values. For example, FIG. 6 depicts anin-progress update to a target yield value for the second field.Additionally, a user computer may select one or more fields in order toapply one or more programs. In response to receiving a selection of aprogram for a particular field, the data manager may automaticallycomplete the entries for the particular field based on the selectedprogram. As with the timeline view, the data manager may update theentries for each field associated with a particular program in responseto receiving an update to the program. Additionally, the data managermay remove the correspondence of the selected program to the field inresponse to receiving an edit to one of the entries for the field.

In an embodiment, model and field data is stored in model and field datarepository 160. Model data comprises data models created for one or morefields. For example, a crop model may include a digitally constructedmodel of the development of a crop on the one or more fields. “Model,”in this context, refers to an electronic digitally stored set ofexecutable instructions and data values, associated with one another,which are capable of receiving and responding to a programmatic or otherdigital call, invocation, or request for resolution based upon specifiedinput values, to yield one or more stored or calculated output valuesthat can serve as the basis of computer-implemented recommendations,output data displays, or machine control, among other things. Persons ofskill in the field find it convenient to express models usingmathematical equations, but that form of expression does not confine themodels disclosed herein to abstract concepts; instead, each model hereinhas a practical application in a computer in the form of storedexecutable instructions and data that implement the model using thecomputer. The model may include a model of past events on the one ormore fields, a model of the current status of the one or more fields,and/or a model of predicted events on the one or more fields. Model andfield data may be stored in data structures in memory, rows in adatabase table, in flat files or spreadsheets, or other forms of storeddigital data.

In some embodiments, agricultural intelligence computer system 130 isprogrammed with or comprises a soil analysis server (“server”) 170. Theserver 170 is further configured to comprise a soil propertyconcentration analysis component 172 and a client interface 174. Each ofthe soil property concentration analysis component 172 and the clientinterface 174 may be implemented as sequences of stored programinstructions. In some embodiments, the soil property concentrationanalysis component 172 is programmed to receive input data from one ormore sources and output current concentration levels of a target analytein the soil or recommendations for adjusting the current concentrationlevels. Input data to the soil property concentration analysis component172 can include data generated by an in-ground sensor system withmodular sensors, processors, and wireless communications components formonitoring properties of field soils introduced above and to be furtherdiscussed in in FIG. 8 , which can comprise one or more of theagricultural apparatus 111, the application controller 114, and theremote sensor 112. An example of such data would be current nitrateconcentration levels in certain soil samples. Additional input data caninclude data received from user computers, such as the field managercomputing device 104 or the cab computer 115, or from the data servercomputer 108, or other data that have been stored in the model datafield data repository 160, such as expected crop yield levels, soilnutrient loss history, historical weather reports or weather forecasts,or records of applying other types of soil nutrients. Output data fromthe soil property concentration analysis component 172 can include whenand how to adjust concentration levels of certain soil nutrients orother elements as well as where such adjustment should be applied. Suchdata can be communicated to the user computers or other remotecomputers.

In some embodiments, the client interface 174 is configured to managecommunication with the in-ground sensor system or a user computer over acommunication network, through the communication layer 132. Thecommunication can include receiving instructions to start real-timefield measurements and desired soil condition or production level from auser computer, sending instructions to the mobile soil analysis systemfor performing real-time measurements of soil element concentrationlevels, receiving the soil measurements from the mobile soil analysissystem, and sending results of analyzing the soil measurements withrespect to the desired soil condition or production level to the usercomputer.

Each component of the server 170 comprises a set of one or more pages ofmain memory, such as RAM, in the agricultural intelligence computersystem 130 into which executable instructions have been loaded and whichwhen executed cause the agricultural intelligence computing system toperform the functions or operations that are described herein withreference to those modules. For example, the soil element concentrationanalysis component 172 may comprise a set of pages in RAM that containinstructions which when executed cause performing soil elementconcentration analysis described herein. The instructions may be inmachine executable code in the instruction set of a CPU and may havebeen compiled based upon source code written in JAVA, C, C++,OBJECTIVE-C, or any other human-readable programming language orenvironment, alone or in combination with scripts in JAVASCRIPT, otherscripting languages and other programming source text. The term “pages”is intended to refer broadly to any region within main memory and thespecific terminology used in a system may vary depending on the memoryarchitecture or processor architecture. In another embodiment, each ofthe components in the server 170 also may represent one or more files orprojects of source code that are digitally stored in a mass storagedevice such as non-volatile RAM or disk storage, in the agriculturalintelligence computer system 130 or a separate repository system, whichwhen compiled or interpreted cause generating executable instructionswhich when executed cause the agricultural intelligence computing systemto perform the functions or operations that are described herein withreference to those modules. In other words, the drawing figure mayrepresent the manner in which programmers or software developersorganize and arrange source code for later compilation into anexecutable, or interpretation into bytecode or the equivalent, forexecution by the agricultural intelligence computer system 130.

Hardware/virtualization layer 150 comprises one or more centralprocessing units (CPUs), memory controllers, and other devices,components, or elements of a computer system such as volatile ornon-volatile memory, non-volatile storage such as disk, and I/O devicesor interfaces as illustrated and described, for example, in connectionwith FIG. 4 . The layer 150 also may comprise programmed instructionsthat are configured to support virtualization, containerization, orother technologies.

For purposes of illustrating a clear example, FIG. 1 shows a limitednumber of instances of certain functional elements. However, in otherembodiments, there may be any number of such elements. For example,embodiments may use thousands or millions of different mobile computingdevices 104 associated with different users. Further, the system 130and/or external data server computer 108 may be implemented using two ormore processors, cores, clusters, or instances of physical machines orvirtual machines, configured in a discrete location or co-located withother elements in a datacenter, shared computing facility or cloudcomputing facility.

2.2. Application Program Overview

In an embodiment, the implementation of the functions described hereinusing one or more computer programs or other software elements that areloaded into and executed using one or more general-purpose computerswill cause the general-purpose computers to be configured as aparticular machine or as a computer that is specially adapted to performthe functions described herein. Further, each of the flow diagrams thatare described further herein may serve, alone or in combination with thedescriptions of processes and functions in prose herein, as algorithms,plans or directions that may be used to program a computer or logic toimplement the functions that are described. In other words, all theprose text herein, and all the drawing figures, together are intended toprovide disclosure of algorithms, plans or directions that aresufficient to permit a skilled person to program a computer to performthe functions that are described herein, in combination with the skilland knowledge of such a person given the level of skill that isappropriate for inventions and disclosures of this type.

In an embodiment, user 102 interacts with agricultural intelligencecomputer system 130 using field manager computing device 104 configuredwith an operating system and one or more application programs or apps;the field manager computing device 104 also may interoperate with theagricultural intelligence computer system independently andautomatically under program control or logical control and direct userinteraction is not always required. Field manager computing device 104broadly represents one or more smartphones, PDA, tablet computingdevice, laptop computer, desktop computer, workstation, or any othercomputing device capable of transmitting and receiving information andperforming the functions described herein. Field manager computingdevice 104 may communicate via a network using a mobile applicationstored on field manager computing device 104, and in some embodiments,the device may be coupled using a cable 113 or connector to the sensor112 and/or controller 114. A particular user 102 may own, operate orpossess and use, in connection with system 130, more than one fieldmanager computing device 104 at a time.

The mobile application may provide client-side functionality, via thenetwork to one or more mobile computing devices. In an exampleembodiment, field manager computing device 104 may access the mobileapplication via a web browser or a local client application or app.Field manager computing device 104 may transmit data to, and receivedata from, one or more front-end servers, using web-based protocols orformats such as HTTP, XML, and/or JSON, or app-specific protocols. In anexample embodiment, the data may take the form of requests and userinformation input, such as field data, into the mobile computing device.In some embodiments, the mobile application interacts with locationtracking hardware and software on field manager computing device 104which determines the location of field manager computing device 104using standard tracking techniques such as multilateration of radiosignals, the global positioning system (GPS), Wi-Fi positioning systems,or other methods of mobile positioning. In some cases, location data orother data associated with the device 104, user 102, and/or useraccount(s) may be obtained by queries to an operating system of thedevice or by requesting an app on the device to obtain data from theoperating system.

In an embodiment, field manager computing device 104 sends field data106 to agricultural intelligence computer system 130 comprising orincluding, but not limited to, data values representing one or more of:a geographical location of the one or more fields, tillage informationfor the one or more fields, crops planted in the one or more fields, andsoil data extracted from the one or more fields. Field manager computingdevice 104 may send field data 106 in response to user input from user102 specifying the data values for the one or more fields. Additionally,field manager computing device 104 may automatically send field data 106when one or more of the data values becomes available to field managercomputing device 104. For example, field manager computing device 104may be communicatively coupled to remote sensor 112 and/or applicationcontroller 114 which include an irrigation sensor and/or irrigationcontroller. In response to receiving data indicating that applicationcontroller 114 released water onto the one or more fields, field managercomputing device 104 may send field data 106 to agriculturalintelligence computer system 130 indicating that water was released onthe one or more fields. Field data 106 identified in this disclosure maybe input and communicated using electronic digital data that iscommunicated between computing devices using parameterized URLs overHTTP, or another suitable communication or messaging protocol.

A commercial example of the mobile application is CLIMATE FIELDVIEW,commercially available from The Climate Corporation, San Francisco,California. The CLIMATE FIELDVIEW application, or other applications,may be modified, extended, or adapted to include features, functions,and programming that have not been disclosed earlier than the filingdate of this disclosure. In one embodiment, the mobile applicationcomprises an integrated software platform that allows a grower to makefact-based decisions for their operation because it combines historicaldata about the grower's fields with any other data that the growerwishes to compare. The combinations and comparisons may be performed inreal time and are based upon scientific models that provide potentialscenarios to permit the grower to make better, more informed decisions.

FIG. 2 illustrates two views of an example logical organization of setsof instructions in main memory when an example mobile application isloaded for execution. In FIG. 2 , each named element represents a regionof one or more pages of RAM or other main memory, or one or more blocksof disk storage or other non-volatile storage, and the programmedinstructions within those regions. In one embodiment, in view (a), amobile computer application 200 comprises account-fields-dataingestion-sharing instructions 202, overview and alert instructions 204,digital map book instructions 206, seeds and planting instructions 208,nitrogen instructions 210, weather instructions 212, field healthinstructions 214, and performance instructions 216.

In one embodiment, a mobile computer application 200 comprises account,fields, data ingestion, sharing instructions 202 which are programmed toreceive, translate, and ingest field data from third party systems viamanual upload or APIs. Data types may include field boundaries, yieldmaps, as-planted maps, soil test results, as-applied maps, and/ormanagement zones, among others. Data formats may include shapefiles,native data formats of third parties, and/or farm management informationsystem (FMIS) exports, among others. Receiving data may occur via manualupload, email with attachment, external APIs that push data to themobile application, or instructions that call APIs of external systemsto pull data into the mobile application. In one embodiment, mobilecomputer application 200 comprises a data inbox. In response toreceiving a selection of the data inbox, the mobile computer application200 may display a graphical user interface for manually uploading datafiles and importing uploaded files to a data manager.

In one embodiment, digital map book instructions 206 comprise field mapdata layers stored in device memory and are programmed with datavisualization tools and geospatial field notes. This provides growerswith convenient information close at hand for reference, logging andvisual insights into field performance. In one embodiment, overview andalert instructions 204 are programmed to provide an operation-wide viewof what is important to the grower, and timely recommendations to takeaction or focus on particular issues. This permits the grower to focustime on what needs attention, to save time and preserve yield throughoutthe season. In one embodiment, seeds and planting instructions 208 areprogrammed to provide tools for seed selection, hybrid placement, andscript creation, including variable rate (VR) script creation, basedupon scientific models and empirical data. This enables growers tomaximize yield or return on investment through optimized seed purchase,placement and population.

In one embodiment, script generation instructions 205 are programmed toprovide an interface for generating scripts, including variable rate(VR) fertility scripts. The interface enables growers to create scriptsfor field implements, such as nutrient applications, planting, andirrigation. For example, a planting script interface may comprise toolsfor identifying a type of seed for planting. Upon receiving a selectionof the seed type, mobile computer application 200 may display one ormore fields broken into management zones, such as the field map datalayers created as part of digital map book instructions 206. In oneembodiment, the management zones comprise soil zones along with a panelidentifying each soil zone and a soil name, texture, drainage for eachzone, or other field data. Mobile computer application 200 may alsodisplay tools for editing or creating such, such as graphical tools fordrawing management zones, such as soil zones, over a map of one or morefields. Planting procedures may be applied to all management zones ordifferent planting procedures may be applied to different subsets ofmanagement zones. When a script is created, mobile computer application200 may make the script available for download in a format readable byan application controller, such as an archived or compressed format.Additionally, and/or alternatively, a script may be sent directly to cabcomputer 115 from mobile computer application 200 and/or uploaded to oneor more data servers and stored for further use.

In one embodiment, nitrogen instructions 210 are programmed to providetools to inform nitrogen decisions by visualizing the availability ofnitrogen to crops. This enables growers to maximize yield or return oninvestment through optimized nitrogen application during the season.Example programmed functions include displaying images such as SSURGOimages to enable drawing of fertilizer application zones and/or imagesgenerated from subfield soil data, such as data obtained from sensors,at a high spatial resolution (as fine as millimeters or smallerdepending on sensor proximity and resolution); upload of existinggrower-defined zones; providing a graph of plant nutrient availabilityand/or a map to enable tuning application(s) of nitrogen across multiplezones; output of scripts to drive machinery; tools for mass data entryand adjustment; and/or maps for data visualization, among others. “Massdata entry,” in this context, may mean entering data once and thenapplying the same data to multiple fields and/or zones that have beendefined in the system; example data may include nitrogen applicationdata that is the same for many fields and/or zones of the same grower,but such mass data entry applies to the entry of any type of field datainto the mobile computer application 200. For example, nitrogeninstructions 210 may be programmed to accept definitions of nitrogenapplication and practices programs and to accept user input specifyingto apply those programs across multiple fields. “Nitrogen applicationprograms,” in this context, refers to stored, named sets of data thatassociates: a name, color code or other identifier, one or more dates ofapplication, types of material or product for each of the dates andamounts, method of application or incorporation such as injected orbroadcast, and/or amounts or rates of application for each of the dates,crop or hybrid that is the subject of the application, among others.“Nitrogen practices programs,” in this context, refer to stored, namedsets of data that associates: a practices name; a previous crop; atillage system; a date of primarily tillage; one or more previoustillage systems that were used; one or more indicators of applicationtype, such as manure, that were used. Nitrogen instructions 210 also maybe programmed to generate and cause displaying a nitrogen graph, whichindicates projections of plant use of the specified nitrogen and whethera surplus or shortfall is predicted; in some embodiments, differentcolor indicators may signal a magnitude of surplus or magnitude ofshortfall. In one embodiment, a nitrogen graph comprises a graphicaldisplay in a computer display device comprising a plurality of rows,each row associated with and identifying a field; data specifying whatcrop is planted in the field, the field size, the field location, and agraphic representation of the field perimeter; in each row, a timelineby month with graphic indicators specifying each nitrogen applicationand amount at points correlated to month names; and numeric and/orcolored indicators of surplus or shortfall, in which color indicatesmagnitude.

In one embodiment, the nitrogen graph may include one or more user inputfeatures, such as dials or slider bars, to dynamically change thenitrogen planting and practices programs so that a user may optimize hisnitrogen graph. The user may then use his optimized nitrogen graph andthe related nitrogen planting and practices programs to implement one ormore scripts, including variable rate (VR) fertility scripts. Nitrogeninstructions 210 also may be programmed to generate and cause displayinga nitrogen map, which indicates projections of plant use of thespecified nitrogen and whether a surplus or shortfall is predicted; insome embodiments, different color indicators may signal a magnitude ofsurplus or magnitude of shortfall. The nitrogen map may displayprojections of plant use of the specified nitrogen and whether a surplusor shortfall is predicted for different times in the past and the future(such as daily, weekly, monthly or yearly) using numeric and/or coloredindicators of surplus or shortfall, in which color indicates magnitude.In one embodiment, the nitrogen map may include one or more user inputfeatures, such as dials or slider bars, to dynamically change thenitrogen planting and practices programs so that a user may optimize hisnitrogen map, such as to obtain a preferred amount of surplus toshortfall. The user may then use his optimized nitrogen map and therelated nitrogen planting and practices programs to implement one ormore scripts, including variable rate (VR) fertility scripts. In otherembodiments, similar instructions to the nitrogen instructions 210 couldbe used for application of other nutrients (such as phosphorus andpotassium), application of pesticide, and irrigation programs.

In one embodiment, weather instructions 212 are programmed to providefield-specific recent weather data and forecasted weather information.This enables growers to save time and have an efficient integrateddisplay with respect to daily operational decisions.

In one embodiment, field health instructions 214 are programmed toprovide timely remote sensing images highlighting in-season cropvariation and potential concerns. Example programmed functions includecloud checking, to identify possible clouds or cloud shadows;determining nitrogen indices based on field images; graphicalvisualization of scouting layers, including, for example, those relatedto field health, and viewing and/or sharing of scouting notes; and/ordownloading satellite images from multiple sources and prioritizing theimages for the grower, among others.

In one embodiment, performance instructions 216 are programmed toprovide reports, analysis, and insight tools using on-farm data forevaluation, insights and decisions. This enables the grower to seekimproved outcomes for the next year through fact-based conclusions aboutwhy return on investment was at prior levels, and insight intoyield-limiting factors. The performance instructions 216 may beprogrammed to communicate via the network(s) 109 to back-end analyticsprograms executed at agricultural intelligence computer system 130and/or external data server computer 108 and configured to analyzemetrics such as yield, yield differential, hybrid, population, SSURGOzone, soil test properties, or elevation, among others. Programmedreports and analysis may include yield variability analysis, treatmenteffect estimation, benchmarking of yield and other metrics against othergrowers based on anonymized data collected from many growers, or datafor seeds and planting, among others.

Applications having instructions configured in this way may beimplemented for different computing device platforms while retaining thesame general user interface appearance. For example, the mobileapplication may be programmed for execution on tablets, smartphones, orserver computers that are accessed using browsers at client computers.Further, the mobile application as configured for tablet computers orsmartphones may provide a full app experience or a cab app experiencethat is suitable for the display and processing capabilities of cabcomputer 115. For example, referring now to view (b) of FIG. 2 , in oneembodiment a cab computer application 220 may comprise maps-cabinstructions 222, remote view instructions 224, data collect andtransfer instructions 226, machine alerts instructions 228, scripttransfer instructions 230, and scouting-cab instructions 232. The codebase for the instructions of view (b) may be the same as for view (a)and executables implementing the code may be programmed to detect thetype of platform on which they are executing and to expose, through agraphical user interface, only those functions that are appropriate to acab platform or full platform. This approach enables the system torecognize the distinctly different user experience that is appropriatefor an in-cab environment and the different technology environment ofthe cab. The maps-cab instructions 222 may be programmed to provide mapviews of fields, farms or regions that are useful in directing machineoperation. The remote view instructions 224 may be programmed to turnon, manage, and provide views of machine activity in real-time or nearreal-time to other computing devices connected to the system 130 viawireless networks, wired connectors or adapters, and the like. The datacollect and transfer instructions 226 may be programmed to turn on,manage, and provide transfer of data collected at sensors andcontrollers to the system 130 via wireless networks, wired connectors oradapters, and the like. The machine alerts instructions 228 may beprogrammed to detect issues with operations of the machine or tools thatare associated with the cab and generate operator alerts. The scripttransfer instructions 230 may be configured to transfer in scripts ofinstructions that are configured to direct machine operations or thecollection of data. The scouting-cab instructions 232 may be programmedto display location-based alerts and information received from thesystem 130 based on the location of the field manager computing device104, agricultural apparatus 111, or sensors 112 in the field and ingest,manage, and provide transfer of location-based scouting observations tothe system 130 based on the location of the agricultural apparatus 111or sensors 112 in the field.

2.3. Data Ingest to the Computer System

In an embodiment, external data server computer 108 stores external data110, including soil data representing soil composition for the one ormore fields and weather data representing temperature and precipitationon the one or more fields. The weather data may include past and presentweather data as well as forecasts for future weather data. In anembodiment, external data server computer 108 comprises a plurality ofservers hosted by different entities. For example, a first server maycontain soil composition data while a second server may include weatherdata. Additionally, soil composition data may be stored in multipleservers. For example, one server may store data representing percentageof sand, silt, and clay in the soil while a second server may store datarepresenting percentage of organic matter (OM) in the soil.

In an embodiment, remote sensor 112 comprises one or more sensors thatare programmed or configured to produce one or more observations. Remotesensor 112 may be aerial sensors, such as satellites, vehicle sensors,planting equipment sensors, tillage sensors, fertilizer or insecticideapplication sensors, harvester sensors, and any other implement capableof receiving data from the one or more fields. In an embodiment,application controller 114 is programmed or configured to receiveinstructions from agricultural intelligence computer system 130.Application controller 114 may also be programmed or configured tocontrol an operating parameter of an agricultural vehicle or implement.For example, an application controller may be programmed or configuredto control an operating parameter of a vehicle, such as a tractor,planting equipment, tillage equipment, fertilizer or insecticideequipment, harvester equipment, or other farm implements such as a watervalve. Other embodiments may use any combination of sensors andcontrollers, of which the following are merely selected examples.

The system 130 may obtain or ingest data under user 102 control, on amass basis from a large number of growers who have contributed data to ashared database system. This form of obtaining data may be termed“manual data ingest” as one or more user-controlled computer operationsare requested or triggered to obtain data for use by the system 130. Asan example, the CLIMATE FIELDVIEW application, commercially availablefrom The Climate Corporation, San Francisco, California, may be operatedto export data to system 130 for storing in the repository 160.

For example, seed monitor systems can both control planter apparatuscomponents and obtain planting data, including signals from seed sensorsvia a signal harness that comprises a CAN backbone and point-to-pointconnections for registration and/or diagnostics. Seed monitor systemscan be programmed or configured to display seed spacing, population andother information to the user via the cab computer 115 or other deviceswithin the system 130. Examples are disclosed in U.S. Pat. No. 8,738,243and US Pat. Pub. 20150094916, and the present disclosure assumesknowledge of those other patent disclosures.

Likewise, yield monitor systems may contain yield sensors for harvesterapparatus that send yield measurement data to the cab computer 115 orother devices within the system 130. Yield monitor systems may utilizeone or more remote sensors 112 to obtain grain moisture measurements ina combine or other harvester and transmit these measurements to the uservia the cab computer 115 or other devices within the system 130.

In an embodiment, examples of sensors 112 that may be used with anymoving vehicle or apparatus of the type described elsewhere hereininclude kinematic sensors and position sensors. Kinematic sensors maycomprise any of speed sensors such as radar or wheel speed sensors,accelerometers, or gyros. Position sensors may comprise GPS receivers ortransceivers, or Wi-Fi-based position or mapping apps that areprogrammed to determine location based upon nearby Wi-Fi hotspots, amongothers.

In an embodiment, examples of sensors 112 that may be used with tractorsor other moving vehicles include engine speed sensors, fuel consumptionsensors, area counters or distance counters that interact with GPS orradar signals, PTO (power take-off) speed sensors, tractor hydraulicssensors configured to detect hydraulics parameters such as pressure orflow, and/or and hydraulic pump speed, wheel speed sensors or wheelslippage sensors. In an embodiment, examples of controllers 114 that maybe used with tractors include hydraulic directional controllers,pressure controllers, and/or flow controllers; hydraulic pump speedcontrollers; speed controllers or governors; hitch position controllers;or wheel position controllers provide automatic steering.

In an embodiment, examples of sensors 112 that may be used with seedplanting equipment such as planters, drills, or air seeders include seedsensors, which may be optical, electromagnetic, or impact sensors;downforce sensors such as load pins, load cells, pressure sensors; soilproperty sensors such as reflectivity sensors, moisture sensors,electrical conductivity sensors, optical residue sensors, or temperaturesensors; component operating criteria sensors such as planting depthsensors, downforce cylinder pressure sensors, seed disc speed sensors,seed drive motor encoders, seed conveyor system speed sensors, or vacuumlevel sensors; or pesticide application sensors such as optical or otherelectromagnetic sensors, or impact sensors. In an embodiment, examplesof controllers 114 that may be used with such seed planting equipmentinclude: toolbar fold controllers, such as controllers for valvesassociated with hydraulic cylinders; downforce controllers, such ascontrollers for valves associated with pneumatic cylinders, airbags, orhydraulic cylinders, and programmed for applying downforce to individualrow units or an entire planter frame; planting depth controllers, suchas linear actuators; metering controllers, such as electric seed meterdrive motors, hydraulic seed meter drive motors, or swath controlclutches; hybrid selection controllers, such as seed meter drive motors,or other actuators programmed for selectively allowing or preventingseed or an air-seed mixture from delivering seed to or from seed metersor central bulk hoppers; metering controllers, such as electric seedmeter drive motors, or hydraulic seed meter drive motors; seed conveyorsystem controllers, such as controllers for a belt seed deliveryconveyor motor; marker controllers, such as a controller for a pneumaticor hydraulic actuator; or pesticide application rate controllers, suchas metering drive controllers, orifice size or position controllers.

In an embodiment, examples of sensors 112 that may be used with tillageequipment include position sensors for tools such as shanks or discs;tool position sensors for such tools that are configured to detectdepth, gang angle, or lateral spacing; downforce sensors; or draft forcesensors. In an embodiment, examples of controllers 114 that may be usedwith tillage equipment include downforce controllers or tool positioncontrollers, such as controllers configured to control tool depth, gangangle, or lateral spacing.

In an embodiment, examples of sensors 112 that may be used in relationto apparatus for applying fertilizer, insecticide, fungicide and thelike, such as on-planter starter fertilizer systems, subsoil fertilizerapplicators, or fertilizer sprayers, include: fluid system criteriasensors, such as flow sensors or pressure sensors; sensors indicatingwhich spray head valves or fluid line valves are open; sensorsassociated with tanks, such as fill level sensors; sectional orsystem-wide supply line sensors, or row-specific supply line sensors; orkinematic sensors such as accelerometers disposed on sprayer booms. Inan embodiment, examples of controllers 114 that may be used with suchapparatus include pump speed controllers; valve controllers that areprogrammed to control pressure, flow, direction, PWM and the like; orposition actuators, such as for boom height, subsoiler depth, or boomposition.

In an embodiment, examples of sensors 112 that may be used withharvesters include yield monitors, such as impact plate strain gauges orposition sensors, capacitive flow sensors, load sensors, weight sensors,or torque sensors associated with elevators or augers, or optical orother electromagnetic grain height sensors; grain moisture sensors, suchas capacitive sensors; grain loss sensors, including impact, optical, orcapacitive sensors; header operating criteria sensors such as headerheight, header type, deck plate gap, feeder speed, and reel speedsensors; separator operating criteria sensors, such as concaveclearance, rotor speed, shoe clearance, or chaffer clearance sensors;auger sensors for position, operation, or speed; or engine speedsensors. In an embodiment, examples of controllers 114 that may be usedwith harvesters include header operating criteria controllers forelements such as header height, header type, deck plate gap, feederspeed, or reel speed; separator operating criteria controllers forfeatures such as concave clearance, rotor speed, shoe clearance, orchaffer clearance; or controllers for auger position, operation, orspeed.

In an embodiment, examples of sensors 112 that may be used with graincarts include weight sensors, or sensors for auger position, operation,or speed. In an embodiment, examples of controllers 114 that may be usedwith grain carts include controllers for auger position, operation, orspeed.

In an embodiment, examples of sensors 112 and controllers 114 may beinstalled in unmanned aerial vehicle (UAV) apparatus or “drones.” Suchsensors may include cameras with detectors effective for any range ofthe electromagnetic spectrum including visible light, infrared,ultraviolet, near-infrared (NIR), and the like; accelerometers;altimeters; temperature sensors; humidity sensors; pitot tube sensors orother airspeed or wind velocity sensors; battery life sensors; or radaremitters and reflected radar energy detection apparatus; otherelectromagnetic radiation emitters and reflected electromagneticradiation detection apparatus. Such controllers may include guidance ormotor control apparatus, control surface controllers, cameracontrollers, or controllers programmed to turn on, operate, obtain datafrom, manage and configure any of the foregoing sensors. Examples aredisclosed in U.S. patent application Ser. No. 14/831,165 and the presentdisclosure assumes knowledge of that other patent disclosure.

In an embodiment, sensors 112 and controllers 114 may be affixed to soilsampling and measurement apparatus that is configured or programmed tosample soil and perform soil chemistry tests, soil moisture tests, andother tests pertaining to soil. For example, the apparatus disclosed inU.S. Pat. Nos. 8,767,194 and 8,712,148 may be used, and the presentdisclosure assumes knowledge of those patent disclosures.

In an embodiment, sensors 112 and controllers 114 may comprise weatherdevices for monitoring weather conditions of fields. For example, theapparatus disclosed in U.S. Provisional Application No. 62/154,207,filed on Apr. 29, 2015, U.S. Provisional Application No. 62/175,160,filed on Jun. 12, 2015, U.S. Provisional Application No. 62/198,060,filed on Jul. 28, 2015, and U.S. Provisional Application No. 62/220,852,filed on Sep. 18, 2015, may be used, and the present disclosure assumesknowledge of those patent disclosures.

2.4. Process Overview-Agronomic Model Training

In an embodiment, the agricultural intelligence computer system 130 isprogrammed or configured to create an agronomic model. In this context,an agronomic model is a data structure in memory of the agriculturalintelligence computer system 130 that comprises field data 106, such asidentification data and harvest data for one or more fields. Theagronomic model may also comprise calculated agronomic properties whichdescribe either conditions which may affect the growth of one or morecrops on a field, or properties of the one or more crops, or both.Additionally, an agronomic model may comprise recommendations based onagronomic factors such as crop recommendations, irrigationrecommendations, planting recommendations, fertilizer recommendations,fungicide recommendations, pesticide recommendations, harvestingrecommendations and other crop management recommendations. The agronomicfactors may also be used to estimate one or more crop related results,such as agronomic yield. The agronomic yield of a crop is an estimate ofquantity of the crop that is produced, or in some examples the revenueor profit obtained from the produced crop.

In an embodiment, the agricultural intelligence computer system 130 mayuse a preconfigured agronomic model to calculate agronomic propertiesrelated to currently received location and crop information for one ormore fields. The preconfigured agronomic model is based upon previouslyprocessed field data, including but not limited to, identification data,harvest data, fertilizer data, and weather data. The preconfiguredagronomic model may have been cross validated to ensure accuracy of themodel. Cross validation may include comparison to ground truthing thatcompares predicted results with actual results on a field, such as acomparison of precipitation estimate with a rain gauge or sensorproviding weather data at the same or nearby location or an estimate ofnitrogen content with a soil sample measurement.

FIG. 3 illustrates a programmed process by which the agriculturalintelligence computer system generates one or more preconfiguredagronomic models using field data provided by one or more data sources.FIG. 3 may serve as an algorithm or instructions for programming thefunctional elements of the agricultural intelligence computer system 130to perform the operations that are now described.

At block 305, the agricultural intelligence computer system 130 isconfigured or programmed to implement agronomic data preprocessing offield data received from one or more data sources. The field datareceived from one or more data sources may be preprocessed for thepurpose of removing noise, distorting effects, and confounding factorswithin the agronomic data including measured outliers that couldadversely affect received field data values. Embodiments of agronomicdata preprocessing may include, but are not limited to, removing datavalues commonly associated with outlier data values, specific measureddata points that are known to unnecessarily skew other data values, datasmoothing, aggregation, or sampling techniques used to remove or reduceadditive or multiplicative effects from noise, and other filtering ordata derivation techniques used to provide clear distinctions betweenpositive and negative data inputs.

At block 310, the agricultural intelligence computer system 130 isconfigured or programmed to perform data subset selection using thepreprocessed field data in order to identify datasets useful for initialagronomic model generation. The agricultural intelligence computersystem 130 may implement data subset selection techniques including, butnot limited to, a genetic algorithm method, an all subset models method,a sequential search method, a stepwise regression method, a particleswarm optimization method, and an ant colony optimization method. Forexample, a genetic algorithm selection technique uses an adaptiveheuristic search algorithm, based on evolutionary principles of naturalselection and genetics, to determine and evaluate datasets within thepreprocessed agronomic data.

At block 315, the agricultural intelligence computer system 130 isconfigured or programmed to implement field dataset evaluation. In anembodiment, a specific field dataset is evaluated by creating anagronomic model and using specific quality thresholds for the createdagronomic model. Agronomic models may be compared and/or validated usingone or more comparison techniques, such as, but not limited to, rootmean square error with leave-one-out cross validation (RMSECV), meanabsolute error, and mean percentage error. For example, RMSECV can crossvalidate agronomic models by comparing predicted agronomic propertyvalues created by the agronomic model against historical agronomicproperty values collected and analyzed. In an embodiment, the agronomicdataset evaluation logic is used as a feedback loop where agronomicdatasets that do not meet configured quality thresholds are used duringfuture data subset selection steps (block 310).

At block 320, the agricultural intelligence computer system 130 isconfigured or programmed to implement agronomic model creation basedupon the cross validated agronomic datasets. In an embodiment, agronomicmodel creation may implement multivariate regression techniques tocreate preconfigured agronomic data models.

At block 325, the agricultural intelligence computer system 130 isconfigured or programmed to store the preconfigured agronomic datamodels for future field data evaluation.

2.5. Implementation Example—Hardware Overview

According to one embodiment, the techniques described herein areimplemented by one or more special-purpose computing devices. Thespecial-purpose computing devices may be hard-wired to perform thetechniques, or may include digital electronic devices such as one ormore application-specific integrated circuits (ASICs) or fieldprogrammable gate arrays (FPGAs) that are persistently programmed toperform the techniques, or may include one or more general purposehardware processors programmed to perform the techniques pursuant toprogram instructions in firmware, memory, other storage, or acombination. Such special-purpose computing devices may also combinecustom hard-wired logic, ASICs, or FPGAs with custom programming toaccomplish the techniques. The special-purpose computing devices may bedesktop computer systems, portable computer systems, handheld devices,networking devices or any other device that incorporates hard-wiredand/or program logic to implement the techniques.

For example, FIG. 4 is a block diagram that illustrates a computersystem 400 upon which an embodiment of the invention may be implemented.Computer system 400 includes a bus 402 or other communication mechanismfor communicating information, and a hardware processor 404 coupled withbus 402 for processing information. Hardware processor 404 may be, forexample, a general-purpose microprocessor.

Computer system 400 also includes a main memory 406, such as arandom-access memory (RAM) or other dynamic storage device, coupled tobus 402 for storing information and instructions to be executed byprocessor 404. Main memory 406 also may be used for storing temporaryvariables or other intermediate information during execution ofinstructions to be executed by processor 404. Such instructions, whenstored in non-transitory storage media accessible to processor 404,render computer system 400 into a special-purpose machine that iscustomized to perform the operations specified in the instructions.

Computer system 400 further includes a read only memory (ROM) 408 orother static storage device coupled to bus 402 for storing staticinformation and instructions for processor 404. A storage device 410,such as a magnetic disk, optical disk, or solid-state drive is providedand coupled to bus 402 for storing information and instructions.

Computer system 400 may be coupled via bus 402 to a display 412, such asa cathode ray tube (CRT), for displaying information to a computer user.An input device 414, including alphanumeric and other keys, is coupledto bus 402 for communicating information and command selections toprocessor 404. Another type of user input device is cursor control 416,such as a mouse, a trackball, or cursor direction keys for communicatingdirection information and command selections to processor 404 and forcontrolling cursor movement on display 412. This input device typicallyhas two degrees of freedom in two axes, a first axis (e.g., x) and asecond axis (e.g., y), that allows the device to specify positions in aplane.

Computer system 400 may implement the techniques described herein usingcustomized hard-wired logic, one or more ASICs or FPGAs, firmware and/orprogram logic which in combination with the computer system causes orprograms computer system 400 to be a special-purpose machine. Accordingto one embodiment, the techniques herein are performed by computersystem 400 in response to processor 404 executing one or more sequencesof one or more instructions contained in main memory 406. Suchinstructions may be read into main memory 406 from another storagemedium, such as storage device 410. Execution of the sequences ofinstructions contained in main memory 406 causes processor 404 toperform the process steps described herein. In alternative embodiments,hard-wired circuitry may be used in place of or in combination withsoftware instructions.

The term “storage media” as used herein refers to any non-transitorymedia that store data and/or instructions that cause a machine tooperate in a specific fashion. Such storage media may comprisenon-volatile media and/or volatile media. Non-volatile media includes,for example, optical disks, magnetic disks, or solid-state drives, suchas storage device 410. Volatile media includes dynamic memory, such asmain memory 406. Common forms of storage media include, for example, afloppy disk, a flexible disk, hard disk, solid-state drive, magnetictape, or any other magnetic data storage medium, a CD-ROM, any otheroptical data storage medium, any physical medium with patterns of holes,a RAM, a PROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip orcartridge.

Storage media is distinct from but may be used in conjunction withtransmission media. Transmission media participates in transferringinformation between storage media. For example, transmission mediaincludes coaxial cables, copper wire and fiber optics, including thewires that comprise bus 402. Transmission media can also take the formof acoustic or light waves, such as those generated during radio-waveand infrared data communications.

Various forms of media may be involved in carrying one or more sequencesof one or more instructions to processor 404 for execution. For example,the instructions may initially be carried on a magnetic disk orsolid-state drive of a remote computer. The remote computer can load theinstructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to computer system 400 canreceive the data on the telephone line and use an infrared transmitterto convert the data to an infrared signal. An infrared detector canreceive the data carried in the infrared signal and appropriatecircuitry can place the data on bus 402. Bus 402 carries the data tomain memory 406, from which processor 404 retrieves and executes theinstructions. The instructions received by main memory 406 mayoptionally be stored on storage device 410 either before or afterexecution by processor 404.

Computer system 400 also includes a communication interface 418 coupledto bus 402. Communication interface 418 provides a two-way datacommunication coupling to a network link 420 that is connected to alocal network 422. For example, communication interface 418 may be anintegrated-services digital network (ISDN) card, cable modem, satellitemodem, or a modem to provide a data communication connection to acorresponding type of telephone line. As another example, communicationinterface 418 may be a local area network (LAN) card to provide a datacommunication connection to a compatible LAN. Wireless links may also beimplemented. In any such implementation, communication interface 418sends and receives electrical, electromagnetic or optical signals thatcarry digital data streams representing various types of information.

Network link 420 typically provides data communication through one ormore networks to other data devices. For example, network link 420 mayprovide a connection through local network 422 to a host computer 424 orto data equipment operated by an Internet Service Provider (ISP) 426.ISP 426 in turn provides data communication services through theworld-wide packet data communication network now commonly referred to asthe “Internet” 428. Local network 422 and Internet 428 both useelectrical, electromagnetic or optical signals that carry digital datastreams. The signals through the various networks and the signals onnetwork link 420 and through communication interface 418, which carrythe digital data to and from computer system 400, are example forms oftransmission media.

Computer system 400 can send messages and receive data, includingprogram code, through the network(s), network link 420 and communicationinterface 418. In the Internet example, a server 430 might transmit arequested code for an application program through Internet 428, ISP 426,local network 422 and communication interface 418.

The received code may be executed by processor 404 as it is received,and/or stored in storage device 410, or other non-volatile storage forlater execution.

3. In-Ground Sensor Systems with Modular Sensors and WirelessConnectivity Components

3.1. Overview of Example Sensor System

FIG. 7 depicts an example in-ground sensor system with modular sensorsand wireless connectivity components that is configured to determinefield properties in soil. In the example of FIG. 7 , an in-groundintegrated sensor system 701 is enclosed in a probe 700. Probe 700includes a sealed housing that protects components of integrated sensorsystem 701 from moisture, dust, and other elements. In-ground integratedsensor system 701 may include one or more sensors 704A-704C, one or moreprocessing units 706A-706B, one or more data transmitters (ortransceivers) 707, and one or more internal or external power supplysources 720. Sensors 704A-704C may be configured to perform an analysisof soil samples 702A-702C, while processing units 706A-706B may use theoutcomes of the analysis to generate results 708. Results 708 may bestored in memory 709 and/or provided to transmitters 707. Results 708may be used to generate output 758.

Transmitters or transceivers 707 may be configured to establishcommunications connections with storage devices 750 and/or computerdevices 740, and to transmit output 758 from transmitters 707 to devices750/740. Power sources 720 may be any type of charge-providingcomponents such as conventional batteries or solar panels that areconfigured to supply electrical voltage to sensors 704A-704C, processingunits 706A-706B, transmitters 707, and memory 709.

Samples 702A-702C are samples of soil that may be detected by integratedsensor system 701 once the system is inserted into soil. For example,sample 702A may be a field soil sample that is detected by sensor 704Aonce sensor 704A is in contact with the soil.

Memory units 709 may be used to store results 708, and optionally tostore a UUID of sensor system 701. The UUID of sensor system 701 may bealso encoded as a QR code and imprinted on an outside wall of probe 700as a mark 705. An example of the QR code representing a UUID of sensorsystem 701 is described in FIG. 9E. The UUID of sensor system 701 may beincluded in output 758 along with results 708. In some embodiments, eachsensor 704A-704C has an associated UUID. The UUIDs may be stored inmemory 709, and/or encoded as QR codes that may be imprinted on theoutside wall of probe 700 as marks 705. For example, if processing unit706A generates results 708 based on soil property measurements receivedfrom sensor 704A, then processor 706A may combine results 708 with aUUID of sensor 704A to form output 758, and transmitter 707 may transmitoutput 758 to devices 750/740.

3.1.1. Modular Sensors

Each of the sensors 704A-704C may include any devices configured tomeasure properties of soil samples 702A-702C. Sensors 704A-704C may beimplemented as modules of integrated sensor system 701, and therefore,sensors 704A-704C are referred to as modular sensors. Sensors 704A-704Cmay include nitrate sensors, capacitive moisture sensors, resistive soilmoisture sensors, time-domain reflectometry moisture sensors, andtemperature sensors. Sensors 704A-704C may also include anemometers tomeasure the speed of the wind and rainfall sensors to measure rainfallprecipitation.

In an embodiment, Sensors 704A-704C are connected to an agriculturalintelligence computer system 130 and/or the agricultural apparatus 111,such as the FIELDVIEW. The data from the sensors may be sent to theFIELDVIEW for processing, and/or may be used by the FIELDVIEW to derivevarious recommendations/assessments for the field soils.

A nitrate sensor is an electronic chemical sensor configured to measurea concentration level of nitrate in soil. The nitrate sensor may beimplemented in a silicon dioxide chip and may include silicon substratesthat are placed on a printed circuit board plate. The plate may have a10-pin female Harwin connector. The substrates, the plate, and theconnector may be enclosed in a cartridge that may be covered, or coated,using epoxy or another sealer to allow only the pins of the connectorprotrude the cartridge. An example of nitrate sensor is described inFIG. 9A.

In some embodiments, each nitrate sensor may comprise a referencefield-effect transistor (REFET) having a first element that isN-sensitive and a second element that is not N-sensitive, the twoelements being packaged adjacent one another. In such an embodiment,calibration of the N-sensor may be achieved by calculating a differencein signal of the two elements, thus indicating the influence of changingN concentration. In some embodiments, a processor may execute storedprograms, retrieved from a storage system, that are configured toreceive millivolt response signals from sensors and convert the signalsto part-per-million measurement data. Embodiments with nitrate sensorsprovide the capability to conduct in-field N measurements and generaterecommendations for fertility treatments in the field based onwirelessly transmitting the N measurements to handheld computing devicesthat are programmed with recommendation programs and/or to cab computersin agricultural apparatus that are similarly programmed to generaterecommendations for side dress or other applications of N in the field.In some embodiments, side dress N recommendations may use the Iowa StateUniversity PSNT-based side dress N recommendation model, implementedusing program instructions in mobile computing devices that are coupledto the sensor systems. Additionally, or alternatively, programinstructions may implement a recommendation engine to use soilproperties obtained in real-time via the sensor system to generate rulesspecific for the then-current field. For example, organic matter ortexture measurements can be used to derive a field-specific N thresholdand conversion rate that can be transformed into a side dress ratevalue. For example, one programmed rule may specify that side dress ratein lbs./acre={0 if PSNT>=25 ppm for the top 1 foot of soil} OR{(25−PSNT)*8 if PSNT<25 ppm for the top 1 foot}.

A capacitive moisture sensor is an electronic device that usescapacitance to measure the dielectric permittivity of soil. Thecapacitive moisture sensor may include an access tube that is made ofPVC and that can be installed in the soil, and a sensing head that mayinclude an oscillator circuit, an annular electrode and fringe-effectcapacitor(s) that are configured to measure the dielectric permittivityof the soil. The output of the capacitive moisture sensor includes thefrequency response of the soil's capacitance due to the soil moisturelevel. An example of the capacitive moisture sensor is described in FIG.9B.

A resistive soil moisture sensor is an electronic device that includestwo probes which are used to measure the volumetric content of water insoil. The two probes are used to generate and measure the current thatpasses through the soil between the probes. As the current passes thesoil, the probes measure the resistance value that can be converted tothe moisture value. When the soil is moist, the soil conducts moreelectricity and therefore, the soil provides less resistance and themoisture level in the soil is relatively high. However, when the soil isdry, the soil conducts less electricity, and therefore, the soilprovides more resistance and the moisture level in the soil isrelatively low.

A time-domain reflectometry (TDR) moisture sensor is an electronicdevice configured to measure water content in soil. The TDR sensorimplements a measurement technique that correlates thefrequency-dependent electric and dielectric properties of soil to theirmoisture content. The technique usually involves inserting the TDRsensor into the soil and applying either a standard waveform analysis tosoil samples to determine the average moisture content along the sensoror a profile analysis to measure moisture content at discrete pointsalong the sensor. An example of the TDR sensor is described in FIG. 9C.

A temperature sensor is an electronic device configured to measuretemperature of soil. The device may provide temperature measurementsderived based an electrical signal. The device may include athermocouple, also referred to as a resistance temperature detector,that includes two dissimilar metals that generate electrical voltagethat is in a direct proportion to changes in temperature of the soil.Examples of the temperature sensor are described in FIGS. 9B and 9D.

In an embodiment, processing units 706A-706B are any type ofcomputer-based processors configured to receive and process data.processing units 706A-706B are enclosed in probe 700 of integratedsensor system 701. processing units 706A-706B may be coupled to sensors704A-704C included in probe 700 and may be configured to receivemeasures of soil properties from sensors 704A-704C. Some processingunits 706A-706B may be part of some of sensors 704A-704C and fabricatedon the same chip as sensors 704A-704C.

Processing units 706A-706B may be configured to receive data fromsensors 704A-704C and process the received data. The processing mayinclude converting data representing measures of soil propertiesdetermined by sensors 704A-704C for soil samples 702A-702C. Theconversion may include determining sizes of the samples, normalizing themeasures of the properties in the samples, and determining theconcentration levels of the properties within a standardized rangeand/or using standardized units. For example, a nitrate concentrationlevel in sample 702A may be expressed as a count of nitrate parts permillion in a standardized size of sample 702A. Once processing units706A-706B determine the concentration levels of the properties in thesamples, the processors may provide results 708 to transmitter 707and/or store results 708 in memory 709.

Results 708 may be stored locally in memory 709 and/or in a removablestorage device (not depicted in FIG. 7 ) such as a secure digital (“SD”)card. An SD card is a non-volatile flash memory card for use in portabledevices.

In an embodiment, transmitters or transceivers 707 transmit results 708directly to an LTE modem (not depicted in FIG. 7 ) or a long range(LoRA) radio arrangement (not depicted in FIG. 7 ). The LoRA is adigital wireless data communication technology developed to utilizeradio frequency bands to communicate data. The LoRA uses sub-gigahertzradio frequency bands like 169 MHz, 433 MHz, 868 MHz and 915 MHz toenable very-long-range transmissions of data with low power consumption.

In-ground integrated sensor system 701 may include transmitters,transceivers or both. The transmitters and transceivers are electronicdevices that are configured to establish communications connections withcomputer devices and transmit electronic data to the computer devicesvia the established connections. The difference between a transmitterand a transceiver is that the transmitter is not configured to receivedata from other devices while the transceiver is configured to handlebi-directional communications with other devices.

If in-ground integrated sensor system 701 includes at least onetransmitter 707, then the transmitter may transmit output data 758 assoon as results 708 are provided to transmitter 707. In thisconfiguration, integrated sensor system 701 may operate in a datapush-mode as transmitter 707 transmits, or pushes, output data 758 outas soon as results 708 are available.

If in-ground integrated sensor system 701 includes at least onetransceiver, then integrated sensor system 701 may be queried by anotherdevice for providing output data 758. In this configuration, integratedsystem 701 may operate in a data pull-mode as the transceiver mayprovide output 758 upon receiving requests for output data 758. In thisconfiguration, integrated system 701 may also operate in a datapush-mode as the transceiver may transmit output data 758 even if norequest for output data 758 is received by the transceiver.

In an embodiment, output data 758 is transmitted from probe 700 to anearby LTE-connected hub (not depicted in FIG. 7 ) in compliance withthe Bluetooth communications protocol, and then from the hub to devices740/750. An example of the hub is a smart hub that is a wireless devicethat uses a wireless phone line and the Internet access to facilitateconnections to the 4G global LTE network via Wi-Fi, LAN and/or a voiceconnection. The smart hub can provide wireless connectivity betweentransmitter 707 and devices 740/750.

In an embodiment, output data 758 is transmitted from probe 700 directlyto an LTE modem (not depicted in FIG. 7 ) or a LoRA ratio arrangement(not depicted in FIG. 7 ). If output data 758 is transmitted to aLoRA-enabled device, then output data 758 is encoded into signals withina certain radio frequency band, and the encoded data is communicated tothe LoRA-enabled device.

Installation of probe 700 usually includes integrating sensors704A-704C, processing units 706A-706B, memory units 709 and othercomponents in probe 700. Once all components are integrated in probe700, one or more batteries may be installed in probe 700. If probe 700uses solar panels, then a photovoltaic solar panel, or panels, may beinstalled on probe 700. The photovoltaic solar panel is usually includedin a photovoltaic module comprising photovoltaic solar cells that absorbsunlight as a source of energy to generate electricity.

Probe 700 of in-ground sensor system 701 may be installed in soil usingmany approaches. According to one approach, probe 700 is inserted into acavity created in the soil using a drill with an auger or using a spadeor a shovel.

Once probe 700 is inserted into the cavity in the soil, the position andlocation of probe 700 may be adjusted or refined. For example, a depthof probe 700 may be adjusted until all sensors installed on probe 700are fully covered by the soil. Once probe 700 is inserted into thecavity and power is provided to probe 700, in-ground sensor system 701included in probe 700 may start generating soil property data.

Output data 758 may include results 708 containing soil property datadetermined for samples 702A-702C. Output data 758 may be provided tocomputer device 740 and displayed on a display 742 of computer device740, Output data 758 may be stored in memory 744 or processed by aprocessor 744 of computer device 740. Examples of computer devices 740include laptops, personal computers, mobile devices, smartphones,tablets, and the like.

In some embodiments, output data 758 is transmitted to storage system750, and used to build a database of information about agriculturalfields, and to build a data bank of agricultural data that can be usedby researchers, crop growers, and agricultural industries. Output data758 may be further analyzed and used to generate recommendations forusers.

In some embodiments, output data 758 may include additional data such aUUID of integrated sensor system 701. Upon receiving output data 758,devices 740/750 may use output data 758 to create soil property maps forthe field to indicate, for example, concentration levels of nitrate,phosphorus and moisture for the field. Based on the maps, devices740/750 may generate agricultural recommendations for the field. Therecommendations may be transmitted to a central server, a user computer,or directly to a computer-based controller that controls agriculturalequipment.

3.2. Process Overview

FIG. 8 depicts an example process that uses an in-ground sensor systemwith modular sensors and wireless connectivity components that isconfigured to determine field properties in soil. The example processmay be executed by components of in-ground sensor system 701, describedin FIG. 7 , but other embodiments of FIG. 8 may interoperate with otherkinds of systems. The process depicted in FIG. 8 may be executed on acontinuous basis, according to a programmed schedule, or in response toreceiving a trigger from an operator or a user. The trigger may begenerated when the user generates a message or instructions andtransmits them wirelessly to the sensors.

In step 802, a sensor system receives one or more soil samples. Forexample, sensor system may receive the samples when any of sensors704A-704C, depicted in FIG. 7 , are in contact with the soil. Forexample, if probe 700 is inserted into the soil, then sensors 704A-704Cmay touch the soil, and thus receive the soil samples.

In step 804, the sensor system determines soil property data in soilsamples. This may include measuring, using sensors 704A-704C, one ormore soil properties in the soil samples, and then computing, usingprocessing units 706A-706B, the soil property data based on themeasures. Depending on the specification of sensors 704A-704C, the soilproperty data may include levels of concentration of nitrate,phosphorus, chlorine, pH, potassium, or other elements present in thesamples.

In step 806, the sensor system uses the soil property data to generateresults 708. Results 708 may include the soil property data and,optionally, a UUID of in-ground sensor system 701, or UUIDs of sensors704A-704C. processing units 706A-706B may retrieve the UUIDs from amemory chip of the in-ground sensor system and combine the soil propertydata with the retrieved UUIDs to form results 708. Results 708 may bestored in memory cache or memory unit 709 of the sensor system.

In step 808, the sensor system establishes a communications connectionwith storage device 750, computer device 740 or a smart hub (notdepicted in FIG. 7 ) that may be used as a proxy for storage device 750and/or computer device 740. The communications connection may beestablished by transmitter 707 of in-ground sensor system 701. Thecommunications connection may be a wireless Wi-Fi-based communicationsconnection, or a wire-based LAN or WAN connection. Communications may beestablished automatically to provide autonomous reporting of soil sensorresult data to other systems, or according to a schedule or in responseto a triggering signal.

Once the communications connection with storage device 750, computerdevice 740, or the hub is established, transmitter 707, in step 810,retrieves results 708 from memory unit 709, and uses results 708 togenerate output 758. In an embodiment, output 758 includes results 708and UUID data of in-ground sensor system 701. Once output 758 isgenerated, transmitter 707 transmits output 758 to devices 750/740 orthe hub. For example, output 758 may be transmitted to a data repositorymaintained by a research laboratory server or to a mobile device ownedby a crop grower.

Output 758 may be provided to computer servers and/or user computers tobe used to improve and enhance agricultural practices, such asfertilizing, seeding, or harvesting. For example, output 758 may be usedto generate or modify agricultural prescriptions for the field. Ifoutput 758 includes, for example, information about a nitrateconcentration level in a field, then output 758 may be used todetermine, or adjust, an amount of the nitrogen-based fertilizer to beapplied to the field to compensate for the nitrate leaching occurredover time.

Output 758 may be transmitted to a computer-based controller thatcontrols agricultural equipment such as seeders and planters. Forexample, output 758 that includes information indicating some pondingwater in a field plot may be transmitted to a computer-based controllerof a seeder and used by the controller to instruct the seeder to avoiddispensing the seeds in the plot covered with water.

In step 812, the sensor system tests whether more testing of the testmaterial or other materials is required. If, in step 814, the sensorsystem determines that more testing is required, then the sensor systemproceeds to performing step 816, in which the sensor system receives oneor more new soil samples and proceeds to performing step 804. However,if no more testing is required at this time, then, in step 818, thesensor system stops executing.

4. Example Implementations

4.1. Handheld Integrated Sensor Systems

FIG. 9A depicts an example in-ground sensor system implemented in ahandheld device and comprising modular sensors, processors, and wirelessconnectivity components. In the depicted example, a handheld device 910includes an in-ground sensors system 701. Handheld device 910 may be aportable device that is convenient to carry and use in the field.Handheld device 910 may be shaped as an elongated probe that has a shaftportion used to host in-ground sensor system 701 and a pin portion usedto insert handheld device 910 into soil.

In an embodiment, handheld device 910 comprises one or more sensors 704,one or more processing units 706, and one or more internal or externalpower sources (not depicted in FIG. 9A).

In some embodiments, handheld device 910 includes a display 912 that maybe configured to display output data calculated by processing units 706.Handheld device 910 may also include a transmitter (or a transceiver)707 configured to establish communications connections between handhelddevice 910 and other computer systems, such as storage systems orcomputer devices (not depicted in FIG. 9A) to facilitate data exchangewith other systems.

Handheld device 910 may be used to calculate soil property data forfield soils. Once handheld device 910 is inserted into a cavity createdin soil, handheld device 910 becomes in contact with soil samples 702.Upon detecting soil samples 702, in-ground sensor system 701 performs ananalysis of content of soil samples 702. Results of the analysis mayinclude information about a concentration level of nitrate or otherelements in the soil. The results may be displayed on display 912, whichmay be equipped with any type of interface, including a graphical userinterface.

If handheld device 910 is equipped with transmitter (or a transceiver)707, then transmitter 707 may electronically transmit the results toother computer systems (not depicted in FIG. 9A).

In an embodiment, in-ground sensor system 701 is implemented in anintegrated circuit that may be enclosed in a sealed cartridge andintegrated with handheld device 910. Because the cartridge-based sensorsystem is portable, sensor system 701 may be used to measure nutrientconcentration levels at any location and at any time, and thus overcomesthe shortcomings of the conventional systems that require sending thesoil samples to laboratories and receiving the results on a delayedbasis.

4.2. Blade-Based Integrated Sensor Systems

FIG. 9B depicts two views of an example in-ground moisture andtemperature sensor system implemented in an in-ground blade andcomprising modular sensors, processors, and wireless connectivitycomponents. The view on the left side is a front view of an examplein-ground blade 940, while the view on the right side is a perspectiveview of example in-ground blade 940.

In the depicted example, in-ground blade 940 includes a transmitter 707,a connector 944, a shaft 946 for storing a temperature sensor and acapacitive moisture sensor, and a blade 948 for inserting in-groundblade 940 into soil 949. In some embodiments, in-ground blade 940includes additional sensors (not depicted in FIG. 9B) such astime-domain reflectometry moisture sensors or resistive soil moisturesensors.

A temperature sensor is an electronic device configured to measuretemperature of soil 949. The temperature sensor may include an RTD thatincludes two dissimilar metals that generate electrical voltage indirect proportion to changes in temperature of the soil. The temperaturesensor may measure the RTD changes in the voltage to determine thechanges in the temperature of soil 949.

A capacitive moisture sensor is an electronic device that usescapacitance to measure the dielectric permittivity of soil 949. Thecapacitive moisture sensor may include an access tube that can beinstalled in the soil, and a sensing head that may include an oscillatorcircuit, an annular electrode and fringe-effect capacitors configured tomeasure the dielectric permittivity of soil 949.

In-ground blade 940 may be either permanently or adjustably insertedinto soil 949. The adjustability provides many benefits since theproperties of soil are not homogeneous throughout the soil. For example,the properties of the soil at the soil depth of 6 inches may bedifferent than the properties of the soil at the soil depth of 12inches.

In an embodiment, a plurality of in-ground blades 940 is used todetermine and compute soil property data for various locationsthroughout a field. A crop grower may use the plurality of in-groundblades 940 to collect soil property data for various plots of the fieldand use the collected information to efficiently manage the field. Forexample, the grower may use the received soil property data to vary theamounts of fertilizer used in the plots, and to adjust the fertilizationschedules depending on the current levels of nutrients in the plots.

FIG. 9C depicts an example in-ground sensor system comprising modularsensors, processors, and wireless connectivity components. In thedepicted example, an in-ground sensor system 950 includes a transmitter707, a connector 954, a shaft 956 for storing, for example, a TDRsensor, and two rods 958 that can be inserted into soil. In someembodiments, in-ground sensor system 950 includes additional sensors(not depicted in FIG. 9B) such as capacitive moisture sensors, nitratesensors, or resistive soil moisture sensors. A TDR sensor is anelectronic device configured to measure moisture content in soil. TheTDR includes parallel rods 958 that act as transmission lines. A voltageis applied to the rods and is reflected to the TDR sensor for analysis.The speed or velocity of the voltage pulse measured along the rods isrelated to the dielectric permittivity of the soil.

FIG. 9D depicts an example in-ground nitrate, moisture, and temperaturesensor system implemented in an in-ground blade and comprising modularsensors, processors, and wireless connectivity components. In thedepicted example, an in-ground sensor system 960 includes transmitter707, a connector 964, shafts 966-968 for storing a nitrate sensor, a TDRsensor, a capacity moisture sensor, and a temperature sensor, and ablade 967 that can be inserted into soil 969. In some embodiments,in-ground sensor system 960 includes additional sensors (not depicted inFIG. 9B). The nitrate sensor, the TDR sensor, the capacity moisturesensor and the temperature sensors are described above.

FIG. 9E depicts an example in-ground sensor system that includes asystem identifier. In the depicted example, an in-ground sensor system970 includes an identifier 974. Identifier 974 includes a QR code thatencodes, for example, a UUID of in-ground sensor system 970. Identifier974 may be a laminated piece of paper that has the QR code imprinted onit. Identifier 974 may be attached to a top portion 972 of in-groundsensor system 970.

FIG. 9F depicts an example in-ground sensor system that includes atransmitter. In the depicted example, an in-ground sensor system 980includes, in addition to sensors, processors, and power supply (notdepicted in FIG. 9F), a transmitter 982. Transmitter 982 may beinstalled in an upper part of in-ground sensor system 980, or at leastabove a lower part of in-ground sensor system 980 that is usuallysubmerged in soil 989. In some embodiments, transmitter 982 may beimplemented as a transceiver that is configured to not only establishcommunications connections with other devices and transmit data to thedevices, but also to receive electronic data from the devices.

5. Extensions and Alternatives

In the foregoing specification, embodiments have been described withreference to numerous specific details that may vary from implementationto implementation. The specification and drawings are, accordingly, tobe regarded in an illustrative rather than a restrictive sense. The soleand exclusive indicator of the scope of the disclosure, and what isintended by the applicants to be the scope of the disclosure, is theliteral and equivalent scope of the set of claims that issue from thisapplication, in the specific form in which such claims issue, includingany subsequent correction.

6. Improvements Provided by Certain Embodiments

In an embodiment, an in-ground sensor system with a plurality ofdifferent integrated modular sensors and wireless connectivitycomponents provides an improved, multi-component system for monitoringmultiple different properties of field soils and wirelessly transmittingsoil property data to other devices. The in-ground sensor system may beconfigured and programmed to determine the soil property data on contactwith soil samples and the soil property data may be automatically andwirelessly transmitted from the in-ground sensor system to otherdevices. The versatility and convenience of the in-ground sensor systemallow overcoming the shortcomings of conventional systems that requiresending soil samples to laboratories and awaiting the results for sometime. Therefore, embodiments can provide in-season soil measurementswith little delay between the time of sampling and the time ofevaluation of the sample. Consequently, growers obtain better, nearreal-time data on soil properties of fields.

Embodiments may provide the benefits of convenient and accuratemonitoring nutrient concentration in soil over time. For example, sincean in-ground sensor system allows monitoring the nutrient concentrationin the soil at any time and as frequently as needed, the system allowstracking the changes in the nutrient concentration in the soilaccurately and precisely. Embodiments may provide the benefits ofhelping farmers and researchers to monitor properties of field soils toimprove agricultural practices. Soil property data provided for a fieldby an in-ground sensor may be used to determine, for example, optimizedamounts of fertilizers for the field and optimized schedules forapplying the fertilizers to the field.

Furthermore, embodiments may be packaged to provide easy installation infields, reliable operation over multiple growth seasons, and autonomousreporting of data.

What is claimed is:
 1. An integrated sensor system comprising: one ormore sensors, installed in an in-ground blade, that are configured todetermine one or more measures of at least one property of soil; one ormore processing units, installed in the in-ground blade, that areconfigured to receive, from the one or more sensors, the one or moremeasures of at least one property of soil, and calculate soil propertydata based on the one or more measures of at least one property of soil;and a transmitter, installed in an in-ground blade, that is configuredto receive the soil property data from the one or more processing units,establish a communications connection with at least one computer device,and automatically transmit, via the communications connection, the soilproperty data to the at least one computer device configured on at leastone agricultural machine.
 2. The integrated sensor system of claim 1,wherein the at least one computer device uses the soil property data tocontrol the at least one agricultural machine as the at least oneagricultural machine performs agricultural tasks in an agriculturalfield; wherein the transmitter is configured to establish a wirelesscommunications connection with the at least one computer device; whereinthe wireless communications connection is configured to communicate datain compliance with any type of wireless communications protocolincluding a Bluetooth communications protocol.
 3. The integrated sensorsystem of claim 1, further comprising: a probe configured to provide ahousing for the one or more sensors, the one or more processing units,and the transmitter; a power supply source configured to supply power tocomponents of the integrated sensor system; wherein the power supplysource includes one or more of: a battery, or a solar panel; one or moreimaging sensors; one or more anemometers; and one or more rainfallsensors.
 4. The integrated sensor system of claim 3, wherein the probeis installed in a cavity created in soil; wherein the probe is poweredup once the power supply source is provided; wherein the probe isinitiated once a probing depth is set.
 5. The integrated sensor systemof claim 3, wherein the probe is installed in the in-ground blade. 6.The integrated sensor system of claim 1, wherein the soil property datacomprises information about one or more time-sensitive soil properties;wherein the soil property data is transmitted to a storage device andused to generate a database repository of information about soil;wherein the soil property data is transmitted to a computer system togenerate one or more agricultural prescriptions for a field; wherein theone or more agricultural prescriptions are provided to one or more userdevices configured to control agricultural equipment.
 7. The integratedsensor system of claim 1, wherein the soil property data is transmittedto a cloud-based storage system for storage; wherein the soil propertydata transmitted to the cloud-based storage system is associated withone or more of: date information indicating a date on which the one ormore measures of at least one property of soil were determined, alocation, one or more universal unique identifiers (“UUIDs”), or weatherinformation.
 8. The integrated sensor system of claim 1, wherein thesoil property data includes one or more of: a phosphorus concentrationlevel, a nitrate concentration level, a potassium concentration level, amoisture level, a rainfall level, a pH level, or a chlorine level. 9.The integrated sensor system of claim 1, wherein the one or more sensorsinclude one or more: a capacitive moisture sensor, a time-domainreflectometry moisture sensor, a temperature sensor, or a nitratesensor.
 10. A computer-implemented method for monitoring properties offield soil using an integrated sensor system, the method comprising:determining, using one or more sensors, installed in an in-ground bladeof an integrated sensor system, one or more measures of at least oneproperty of soil; receiving, by one or more processing units, installedin the in-ground blade of the integrated sensor system, the one or moremeasures of at least one property of soil from the one or more sensors;calculate, by the one or more processing units, soil property data basedon the one or more measures of at least one property of soil; receiving,by a transmitter, installed in the in-ground blade of the integratedsensor system, the soil property data from the one or more processingunits; establishing, by the transmitter, a communications connectionwith at least one computer device; and automatically transmitting, bythe transmitter, the soil property data via the communicationsconnection to the at least one computer device configured on at leastone agricultural machine.
 11. The computer-implemented method of claim10, wherein the at least one computer device uses the soil property datato control the at least one agricultural machine as the at least oneagricultural machine performs agricultural tasks in an agriculturalfield; wherein the transmitter is configured to establish a wirelesscommunications connection with the at least one computer device; whereinthe wireless communications connection is configured to communicate datain compliance with any type of wireless communications protocolincluding a Bluetooth communications protocol.
 12. Thecomputer-implemented method of claim 10, wherein the one or moresensors, the one or more processing units, and the transmitter arehoused in a probe of the integrated sensor system; wherein the probeprotects components installed inside the probe from moisture, dust, andother elements; wherein power is supplied to components of theintegrated sensor system by a power supply source which includes one ormore of: a battery, or a solar panel; wherein the integrated sensorsystem further comprises one or more of: an imaging sensor, ananemometer, or a rainfall sensor.
 13. The computer-implemented method ofclaim 12, wherein the probe is installed in a cavity created in soil;wherein the probe is powered up once the power supply source isprovided; wherein the probe is initiated once a probing depth is set.14. The computer-implemented method of claim 12, wherein the probe isinstalled in the in-ground blade.
 15. The computer-implemented method ofclaim 10, wherein the soil property data comprises information about oneor more time-sensitive soil properties; wherein the soil property datais transmitted to a storage device and used to generate a databaserepository of information about soil; wherein the soil property data istransmitted to a computer system to generate one or more agriculturalprescriptions for a field; wherein the one or more agriculturalprescriptions are provided to one or more user devices configured tocontrol agricultural equipment.
 16. The computer-implemented method ofclaim 10, wherein the soil property data is transmitted to a cloud-basedstorage system for storage; wherein the soil property data transmittedto the cloud-based storage system is associated with one or more of:date information indicating a date on which the one or more measures ofat least one property of soil were determined, a location, one or moreuniversal unique identifiers (“UUIDs”), or weather information.
 17. Thecomputer-implemented method of claim 10, wherein the soil property dataincludes one or more of: a phosphorus concentration level, a nitrateconcentration level, a potassium concentration level, a moisture level,a pH level, a rainfall level, or a chlorine level.
 18. Thecomputer-implemented method of claim 10, wherein the one or more sensorsinclude one or more: a capacitive moisture sensor, a time-domainreflectometry moisture sensor, a temperature sensor, or a nitratesensor.